Flexible data anonymization using ARX—Current status and challenges ahead
The race for innovation has turned into a race for data. Rapid developments of new
technologies, especially in the field of artificial intelligence, are accompanied by new ways …
technologies, especially in the field of artificial intelligence, are accompanied by new ways …
[HTML][HTML] Evaluating identity disclosure risk in fully synthetic health data: model development and validation
K El Emam, L Mosquera, J Bass - Journal of medical Internet research, 2020 - jmir.org
Background There has been growing interest in data synthesis for enabling the sharing of
data for secondary analysis; however, there is a need for a comprehensive privacy risk …
data for secondary analysis; however, there is a need for a comprehensive privacy risk …
Linking sensitive data
Sensitive personal data are created in many application domains, and there is now an
increasing demand to share, integrate, and link such data within and across organisations in …
increasing demand to share, integrate, and link such data within and across organisations in …
An ethics framework for big data in health and research
Ethical decision-making frameworks assist in identifying the issues at stake in a particular
setting and thinking through, in a methodical manner, the ethical issues that require …
setting and thinking through, in a methodical manner, the ethical issues that require …
Privacy-preserving process mining in healthcare
Process mining has been successfully applied in the healthcare domain and has helped to
uncover various insights for improving healthcare processes. While the benefits of process …
uncover various insights for improving healthcare processes. While the benefits of process …
A systematic overview on methods to protect sensitive data provided for various analyses
In view of the various methodological developments regarding the protection of sensitive
data, especially with respect to privacy-preserving computation and federated learning, a …
data, especially with respect to privacy-preserving computation and federated learning, a …
Measuring re-identification risk using a synthetic estimator to enable data sharing
Background One common way to share health data for secondary analysis while meeting
increasingly strict privacy regulations is to de-identify it. To demonstrate that the risk of re …
increasingly strict privacy regulations is to de-identify it. To demonstrate that the risk of re …
Evaluating the re-identification risk of a clinical study report anonymized under EMA Policy 0070 and Health Canada Regulations
J Branson, N Good, JW Chen, W Monge, C Probst… - Trials, 2020 - Springer
Background Regulatory agencies, such as the European Medicines Agency and Health
Canada, are requiring the public sharing of clinical trial reports that are used to make drug …
Canada, are requiring the public sharing of clinical trial reports that are used to make drug …
A vulnerability assessment framework for privacy-preserving record linkage
The linkage of records to identify common entities across multiple data sources has gained
increasing interest over the last few decades. In the absence of unique entity identifiers …
increasing interest over the last few decades. In the absence of unique entity identifiers …
Synthetic data for open and reproducible methodological research in social sciences and official statistics
JP Burgard, JP Kolb, H Merkle, R Münnich - AStA Wirtschafts-und …, 2017 - Springer
Open and reproducible research receives more and more attention in the research
community. Whereas empirical research may benefit from research data centres or scientific …
community. Whereas empirical research may benefit from research data centres or scientific …